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Immersive Analytics: Exploring Future Visualization and Interaction Technologies for Data Analytics

Benjamin Bach, University of Edinburgh, UK / Harvard University, MA
Maxime Cordeil, Monash University, VIC
Tim Dwyer, Monash University, VIC
Bongshin Lee, Microsoft Research
Bahador Saket, Georgia Tech
Alex Endert, Georgia Tech
Christopher Collins, University of Ontario Institute of Technology
Sheelagh Carpendale, University of Calgary


Immersive Analytics is a new multidisciplinary initiative to explore future visualization and interaction technologies for data analytics. Immersive Analytics aims to bring together researchers in Information Visualization, Visual Analytics, Virtual and Augmented Reality and Natural User Interfaces. This workshop looks at immersive technologies (e.g., AR, VR, Mixed reality, NUIs, large displays), scenarios, theories and frameworks, collaboration, physical and tangible visualization, as well as interaction techniques.

Discovery Jam

David Rogers, Los Alamos National Lab
Dan Keefe, University of Minnesota
Francesca Samsel, University of Texas at Austin
Miriah Meyer, University of Utah
Cecilia Aragon, University of Washington


You’ve heard of Game Jams and Hack-a-thons–DiscoveryJam brings this same intense, hands-on approach to scientific discovery. Our full day workshop brings scientists together with VIS participants in an interactive day-long workshop to create innovative approaches to scientific discovery problems. Each DiscoveryJam scientist is matched with a small group of attendees. In the morning each group holds interactive discussions with their scientist about specific data and science problems. In the afternoon, each group hacks away on the scientist’s data. We’ll create sketches, prototypes, and sample visualizations, and then present them to the entire workshop. You’ll leave the workshop with skills for communicating with scientists, approaches to cross-disciplinary collaboration, and research ideas to pursue further.
Bring your laptop and your favorite vis tools to dig into data with us.

DSIA: Data Systems for Interactive Analysis

Remco Chang, Tufts University
Danyel Fisher, Microsoft Research
Jeffrey Heer, University of Washington
Carlos Scheidegger, University of Arizona


DSIA brings together researchers at the intersection of databases, machine learning, and interactive visualization. These three areas have important things to say to each other. Modern data visualization depends on the cutting edge of both database and machine learning research: database researchers are exploring techniques for storing and querying massive amounts of data; machine learning techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis procedures. This workshop explores the idea that the next generation of database, machine learning, and interactive visualization systems should not be designed in isolation. For example, machine learning techniques might recommend improved data transformation and visual encoding decisions. Or, database query optimizers might take advantage of perceptual constraints, while prefetching methods reduce latency by modeling likely interactions. This workshop seeks to increase cross-pollination between these fields.

DECISIVe 2017: 2nd Workshop on Dealing with Cognitive Biases in Visualizations

Geoffrey Ellis, University of Konstanz, Germany
Evanthia Dimara, Inria Saclay, France
Donald Kretz, Applied Research Associates, USA
Alex Endert, Georgia Tech, USA


We make thousands of subconscious decisions daily and often apply simplified rules or heuristics to speed up the process. Most of these are good enough, however when there is some uncertainty we can make what appears to be irrational decisions, leading to inaccurate judgements, also known as cognitive biases. Over the last 40 years, hundreds of cognitive biases have been documented, such as the confirmation bias, where people unconsciously seek out information that confirms their current belief, ignoring information to the contrary. Despite a growing awareness of the detrimental effects of cognitive biases on decision making, there is little work on how to detect this behaviour in those who use visualisation-based applications and even less on how to minimise their effect. The aim of this workshop is to bring together people from a wide range of disciplines such as information visualisation, visual analytics, software engineering, cognitive psychology and decision science, as well as those close to end-user groups like intelligence analysts and medical practitioners, to explore some of the ways in which cognitive biases impact user performance and share ideas about practical ways to reduce or overcome these potentially harmful effects, especially in adapting the tools developers design and build.

2nd Pedagogy of Data Visualization Workshop

Alark Joshi, University of San Francisco
Eytan Adar, University of Michigan
Enrico Bertini, New York University
Sophie Engle, University of San Francisco
Marti Hearst, University of California Berkeley
Daniel Keefe, University of Minnesota


The pedagogy of data visualization is becoming increasingly important as data visualization techniques and tools proliferate. In this workshop, we propose to create a community of practice that provides a structured medium to learn from data visualization teaching strategies from each other. The focus is on sharing innovations in the classroom when teaching data visualization. The half-day interactive workshop will include lightning talks/demonstrations followed by breakout sessions focused on topics related to teaching large classes, teaching at a liberal arts college, teaching a professional masters’ course, and so on.

2nd Workshop on Visualization for the Digital Humanities

Stefan Janicke, Leipzig University, Germany
Christopher Collins, University of Ontario Institute of Technology, Canada
Michael Correll, University of Washington, USA
Mennatallah El-Assady, University of Konstanz, Germany
Daniel Keim, University of Konstanz, Germany
David Wrisley, New York University Abu Dhabi, UAE


The first Workshop on Visualization for the Digital Humanities at VIS 2016 created a new platform to discuss challenges in the emerging digital humanities field. The 2nd workshop this year aims (1) to single out new research directions in visualization for the digital humanities, (2) to familiarize the visualization research community with the problems faced by digital humanities researchers, and (3) to establish future collaborations between visualization and digital humanities scholars.

VADL 2017: Workshop on Visual Analytics for Deep Learning

Jaegul Choo, Korea University
Shixia Liu, Tsinghua University
Jason Yosinski, Uber AI Labs
Deokgun Park, University of Maryland, College Park


VADL 2017, the workshop on visual analytics for deep learning, is a half-day workshop held in conjunction with the IEEE VIS 2017 Conference. The primary goal of the workshop is to bridge the gap by bringing together researchers from both the machine learning and visual analytics fields, which allows us to push the boundary of deep learning. The workshop should provide an opportunity to discuss and explore ways to harmonize the power of automated techniques and exploratory nature of interactive visualization.

BPViz: Broadening Participation in Visualization Workshop

Vetria Byrd, Purdue University
Donna Cox, University of Illinois Urbana Champaign


Visualization plays an important role in all levels of scholarship, and across interdisciplinary, research and social landscapes. It is imperative that the importance and benefits of a field with such far reaching impact embrace the diverse demographic of the future workforce for whom data visualization skills will be needed if not required. In order to meet the growing demand for persons with capacity to utilize data visualization to solve complex problems in research and in the workforce exposure to data visualization at all levels is essential. This workshop aims to be a catalyst for broadening participation of women, members of underrepresented groups and underrepresented disciplines in visualization, fostering a community of current and future scholars with interests in visualization through mentoring and encouraging participants to consider visualization as a career path. The workshop is designed to inform, inspire and encourage participants, specifically participants historically underrepresented at the conference, to engage in the multidisciplinary dynamics of visualization.

Vis in Practice - Visualization Solutions in the Wild

Bernd Hentschel, RWTH Aachen University Daniela Oelke, Siemens AG Justin Talbot, Tableau Research


The 2017 ViP Workshop on Visualization Solutions in the Wild is an opportunity for visualization practitioners and researchers to meet and share experiences, insights, and ideas in applying the latest visualization and visual analytics research to real world problems. It targets work at the interface between visualization research and specific application domains. It is highly interdisciplinary and focused on delivering actual value to users. This year, we specifically focus on visualization solutions in the wild, i.e. on tools, systems, or frameworks which are actively used. The workshop will cover all aspects from their initial conception and design, the process of getting them into use, and the long-term work of extending and sustaining them.